DEFICIENCIESIn the IPCC’s Special Report on 1.5 Degrees
J. Ray Bates
with a foreword by Dr Edward Walsh
Revised and updated

The Global Warming Policy Foundation
GWPF Briefing 36

DEFICIENCIESIn the IPCC’s Special Report on 1.5 Degrees
J. Ray Bates© Copyright 2018 The Global Warming Policy Foundation

Contents
Forewordvii

About the author
Note to revised version

viii
viii

1

Introduction

1

2

Departure from the IPCC’s Fifth Assessment Report13

Lines of evidence

14

SR1.5’s main lines of evidence for anthropogenic warming

2

5

Related lines of evidence: observational
Atmospheric temperature evolution observed by satellite
Observations of ocean warming

4
4
6

6

Related lines of evidence: GCM modelling
Model tuning (setting of parameters)
Some recent independent estimates of climate sensitivity

6
6
9

7

Conclusions

10

Notes

12

Foreword
By Dr Edward WalshThis paper presents an evidence-based critique of some central aspects of the recent Special Report on a Global Warming of 1.5 ◦ C (SR1.5) issued by the Intergovernmental Panel on
Climate Change (IPCC). The author, Professor Ray Bates, is an eminent scientist with a lifetime of international experience in weather and climate research; at MIT, as a senior scientist
at NASA and as professor of meteorology at the Niels Bohr Institute, Copenhagen, and at
University College Dublin. His independent scrutiny points to a lack of scientific rigour andbalance in key aspects of the SR1.5 report. Specifically, he presents compelling evidence that
the SR1.5 report is deficient in three regards:• It departs from the IPCC (2013) Fifth Assessment in the direction of an increased senseof planetary emergency without giving rigorous scientific reasons for doing so.
• Crucial research evidence, accumulated since the IPCC Fifth Assessment (2013), significantly reduces the prospect of a looming emergency. This evidence has not beentaken into account; nor is it even referred to in the SR1.5 report.
• The disturbing revelation of the widespread practice of ‘tuning’ global climate models
to achieve desired results, disclosed since the Fifth Assessment, has not been referred
to either.
The importance of adherence to the highest scientific standards on the part of the IPCC in
its periodic reports can hardly be overemphasised. Governments rely on the scientific objectivity of these reports to make crucial decisions related to the economies of their countries
and the wellbeing of their people. Policymakers should carefully reflect on the significant
deficiencies identified in the report before considering implementing its recommendations.
The Global Warming Policy Foundation is to be commended for publishing this important paper. It deserves a wide audience.
Dr. Edward Walsh is Founding President of the University of Limerick and has served as chairman of both Ireland’s National Council for Science Technology and Innovation and of Ireland’s
National Allocation Advisory Group (Carbon Trading).

vii

About the author
Professor J. Ray Bates is Adjunct Professor of Meteorology in the Meteorology and Climate
Centre at University College Dublin. He was formerly Professor of Meteorology at the Niels
Bohr Institute, University of Copenhagen, and a Senior Scientist at NASA’s Goddard Space
Flight Centre. In his early career he was Head of Research at the Irish Meteorological Service.
He obtained a bachelor’s degree in physics at University College Dublin and a PhD in meteorology at MIT. His PhD supervisor at MIT was Jule G. Charney, chairman of the committeethat wrote the 1979 ‘Charney Report’ on the effects of carbon dioxide on climate. Professor
Bates has been the recipient of a number of awards for his scientific work, including the 2009
Vilhelm Bjerknes Medal of the European Geosciences Union. He is a former President of the
Irish Meteorological Society. He has served as an Expert Reviewer of the IPCC’s Third andFifth Assessment Reports. He is a member of the Royal Irish Academy and the Academia Europaea and a Fellow of the American Meteorological Society and the Royal MeteorologicalSociety.

Note to revised version
This is a revised version of the original document of the same name published by the Global
Warming Policy Foundation on 20 December 2018. It contains some clarifications that arosein the context of discussions with colleagues. The main conclusions are unchanged.

viii

1

Introduction

The recent special report of the Intergovernmental Panel on Climate Change, known as
SR1.5,1 goes far beyond all its previous publications in raising the level of alarm about climate change and in calling for drastic action to combat it. The report adopts the standpointthat the essential aspects of climate science are settled and then conflates what it sees as anecessary policy response with ethical issues of sustainable development, poverty eradication and reducing inequalities.
The report calls for radical changes in the world’s economy to achieve zero carbon emissions by mid-century. Given the extremely costly and highly disruptive changes this courseof action would entail, the rigour of the underlying scientific case should be beyond question. Here, some central aspects of SR1.5 are examined to see whether the report exhibits alevel of scientific rigour commensurate with the scale of its prescribed course of action. The
conclusion, based on the evidence, is that it does not.

2

Departure from the IPCC’s Fifth Assessment Report

The IPCC’s assessment reports have each been presented in three parts, representing Working Group I (The Physical Science Basis), Working Group II (Impacts and Adaptation) andWorking Group III (Mitigation of Climate Change). For SR1.5, these three working groups
were merged to produce a generalized report, with a consequent lack of focus on a purely
scientific analysis.
The central attribution statement of Working Group I in the Fifth Assessment Report 2(hereafter WGI AR5) was as follows:
It is extremely likely that more than half of the observed increase in global average surface temperature from 1951 to 2010 was caused by the anthropogenic increase in greenhouse gas concentrations and other anthropogenic forcings together. The best estimateof the human-induced contribution to warming is similar to the observed warming overthis period.

This statement arises primarily from a detection and attribution analysis applied to global
climate model (GCM) simulations.3 It does not attribute the substantial early 20th century
warming (1910–1945) to anthropogenic effects. Regarding this early warming, the reportconcluded (Section 10.3.1.1.3, p. 887):
It remains difficult to quantify the contribution to this warming from internal variability,
natural forcing and anthropogenic forcing, due to forcing and response uncertainties
and incomplete observational coverage.

In contrast to this caution, SR1.5 portrays essentially all the global warming observed since
the late 19th century4 as being human-induced (see Figure 1). 5 This major departure fromthe Fifth Assessment is presented without any rigorous justification.

3

Lines of evidence

A phrase much used by the IPCC is ‘lines of evidence’. Implicit in this phrase is the realistic acknowledgement that there is much in climate science that is not known with certainty andwhich perhaps never can be. Something that is known with certainty is that the concentrations of carbon dioxide and other trace gases that trap heat radiation at infrared wavelengths in the atmosphere are increasing as a result of human activities. Balancing this, it is1Frequently Asked Questions

FAQ 1.2 (continued)

FAQ1.2:How close are we to 1.5°C?
FAQ

Human-induced warming reached approximately 1°C above
pre-industrial levels in 2017

2.00

Current
warming rate

Global temperature change
relative to 1850-1900 (°C)

1.75
1.50

2017

1.25
1.00

Human-induced
warming

Climate uncertainty
for 1.5°C pathway

0.75
0.50
Observed
warming

0.25
0.00
1960

1980

2000

2020

2040

2060

2080

2100

FAQ 1.2, Figure 1 | Human-induced warming reached approximately 1°C above pre-industrial levels in 2017. At the present rate, global temperatures would
reach 1.5°C around 2040. Stylized 1.5°C pathway shown here involves emission reductions beginning immediately, and CO2 emissions reaching zero by 2055.

Figure 1: SR1.5 portrayed essentially all global warming above pre-industrial levels as manmade.
Reproduced from SR1.5, Chapter 1, FAQ 1.2, Figure 1, p. 82. The original caption reads‘Human-induced warming reached approximately 1 ◦ C above pre-industrial levels in 2017.’

also known that the dominant greenhouse gas (GHG) in the atmosphere is naturally occurring water vapour, which is far more abundant than the trace gases. When air rises and cools,
the water vapour it contains condenses into clouds, which affect the greenhouse propertiesof the atmosphere in major ways. Quantifying cloud radiative effects with precision, however, is beyond the capability of present day climate science. For as long as this remains thecase, modelling the climate system’s response to increasing GHG emissions will remain anarea of uncertainty.

4 SR1.5’s main lines of evidence for anthropogenic
warming
In its Summary for Policymakers (SPM), the SR1.5 report presents a plot of observed and8modelled
global mean surface temperature 6 (GMST) for the years 1960–2017 (Figure 2). The
solid orange line shows the modelled central estimate of anthropogenic global warming
up to 2017. The stated modelling method is a multiple regression, in which the dependent
variable is the observed GMST and the independent variables are the estimated global responses to total anthropogenic forcing and to natural (combined volcanic and solar) forcing, these responses being calculated using a simple globally-averaged impulse-responsemodel. The central estimate portrays anthropogenic global warming as markedly accelerating, the rate of warming increasing from about 0.04 ◦ C/decade at the beginning of the period2Figure 2: How SR1.5 portrayed observed and modelled temperatures since 1960.
Observed monthly GMST, grey line up to 2017 (from the HadCRUT4, GISTEMP, Cowtan & Way,
and NOAA datasets) and model-estimated anthropogenic global warming (solid orange line up
to 2017, with orange shading indicating assessed likely range). Source: SR1.5, Figure SPM.1.

to about 0.22◦ C/decade at the end. The agreement shown in the figure between the observations (with interannual variations smoothed out) and the modelled central estimate of theanthropogenic warming is close, suggesting that strong confidence can be placed in boththe indicated acceleration of the warming and its modelled anthropogenic origin.
In its Chapter 1, the SR1.5 report provides further evidence suggesting the recent warming is anthropogenic. It does this by including results of GCM simulations along with theresults of the simple model, in this case for the years 1850–2017 (Figure 3). The GCM results
again show good agreement with the observed warming in recent decades.
However, the picture of global warming for the longer period 1850–2017 shown in Figure 3 is much more complex than the picture for the recent period 1960–2017 shown in
Figure 2. The longer-term observational picture is no longer a simple one of accelerating
warming. The observational data presented in Figure 3 show that prior to 1960, global cooling took place over the 25-year period 1945–1970. Prior to that, between 1910 and 1945,
there was another period of significant global warming. This early 20th-century warming
occurred before anthropogenic GHGs exerted a major influence. Prior to that again, there3was another multi-decadal period of cooling. Figure 3 clearly indicates the existence of substantial natural variability of GMST that is independent of GHGs.
Furthermore, the modelled temperatures – simple model or GCM – do not agree wellwith the observational data over the longer period. This lack of agreement is particularly
evident during the early 20th century warming period. This was clearly a factor (in the GCM
context) influencing IPCC AR5 not to attribute the early 20th century warming to anthropogenic causes (Section 2 above). In contrast, despite a similar lack of agreement between
the simple model output and the observational data during this period, SR1.5 concludes
that this early warming was very largely anthropogenic.
Questions arise as to why the human-induced warming given by the simple model agrees
so well with the observed GMST during the period 1960–2017, giving an even better fit thanthe GCM-based results, and as to why these quantities disagree so markedly during the early
20th century warming period. All quantities in the simple model represent global averages
and all its input data are global averages; thus the simple model allows for no effects of spatial variation. It therefore allows no scope for preventing erroneous attribution to globallyaveraged forcing of any global warming fluctuation that might in reality result from a spatially varying temperature pattern, whereas GCMs – despite their limitations – would allow
scope for this. The simple model is also constrained by the fact that its explanatory variables
are modelled responses to anthropogenic forcing and to natural forcing. The sum of natural solar and volcanic forcings had very little trend over the 1960–2017 period. 7 Internalvariability was not treated as an explanatory variable in deriving the central estimate of thehuman-induced warming (though it was used in estimating its likely range). These factors
appear likely to influence the recent degree of fit between model output and observations
and to be relevant in any attempt to explain the difference in this regard between the recent
and the early 20th century period.
In what follows, the rigour of the SR1.5 report will be examined further in relation tosome of the matters discussed above. Evidence regarding global data will be considered in
Section 5, while evidence regarding GCM modelling will be considered in Section 6.

5 Related lines of evidence: observational
Atmospheric temperature evolution observed by satellite
The marked acceleration in the rate of surface warming in recent years, as suggested by
Figures 1–3, is not apparent in satellite-based measurements of lower tropospheric temperatures (some kilometres above the ground), an example of which is shown in Figure 4.
In fact, the satellite temperatures, though showing a warming trend of 0.13 ◦ C /decade
over the full observational period 1979–2018, show very little warming since the year 2000.
Scafetta et al. have performed a statistical analysis in which the prominent El Niño signal in
the satellite temperatures in the period 2000-2016 is removed from the record, 12 and foundthat the remaining warming trend in this period is only of the order of 0.04 ◦ C /decade.13
The SR1.5 report does not discuss satellite-observed temperature trends and does notaddress the problem of why they differ so markedly from the GMSTs. This is a serious defect, since there are strong reasons to believe that satellite temperatures are more reliableindicators of the true rate of global warming than the GMST; the satellite temperature measurements have near-global coverage while surface temperature measurements are sparseand irregularly distributed.
4

even this product is spatially incomplete in the early record), while
NOAAGlobalTemp (Vose et al., 2012) and HadCRUT (Morice et al.,2012) are progressively closer to a simple average of available
observations. Since the AR5, considerable effort has been devoted
to more sophisticated statistical modelling to account for the impact

2012 based on a linear trend. This quantity was quoted as 0.85°C in
the AR5. Hence the inclusion of the Cowtan-Way dataset does not
introduce any inconsistency with the AR5, whereas redefining GMST
to represent global SAT could increase this figure by up to 20% (Table
1.1, blue lines in Figure 1.2 and Richardson et al., 2016).

Figure 1.2 | Evolution of global mean surface temperature (GMST) over the period of instrumental observations. Grey shaded line shows monthly mean GMST
3: HowGISTEMP
SR1.5and
portrayed
the observed
and modelledtemperatures
since
1850.
Figurein the HadCRUT4,NOAAGlobalTemp,
Cowtan-Way datasets,
expressed as departuresfrom 1850–1900,
with varying grey line
thickness
indicating inter-dataset
range. All observational Evolution
datasets shown
represent
GMST
asaweighted
averageofnear
surfaceairtemperature
over
land
and
sea
surfacetemperature
over oceans. Humanof GMST over the period of instrumental observations. Grey shaded line shows
induced (yellow) andtotal(humanandnaturally-forced,orange)contributions
to
these
GMST
changesareshown
calculated
following
Otto
et
al.
(2015)
observed monthly mean GMST in the HadCRUT4, NOAAGlobalTemp, GISTEMP and Cowtan-Way and Haustein et al.
(2017). Fractional uncertainty in the level of human-induced warming in 2017 is set equal to ±20% based on multiple lines of evidence. Thin blue lines show the modelled
datasets, expressed as departures from 1850–1900. Modelled human-induced (yellow) andglobal mean surface air temperature (dashed) and blended surface air and sea surface temperature accounting for observational coverage (solid) from the CMIP5 historical
total (humannaturally-forced,orange)contributions
these
GMST
changesshown, fluctuations over theensemble average extended
with RCP8.5and
forcing(Cowtan et al., 2015;
Richardson
et al., 2018). Thetopink
shading
indicates
a range arefor temperature
89
Thin
Haustein
et al.
lines(Kirtman
show etthe
GMST
following
Holocene (Marcott etcalculatedal., 2013). Light
green plumeOttoshowsettheal.
AR5andprediction
for average
GMSTover blue
2016–2035
al.,modelled2013). See Supplementary
Material 1.SM forfurther details.
(dashed) and blended surface air and sea surface temperature accounting for observational

Anomaly (◦ C)

coverage (solid) from the CMIP5 historical ensemble average extended with RCP8.5 forcing.
Light green plume shows the AR5 prediction for average GMST over 2016–2035. Note that thein the HadCRUT4 dataset, average temperatures over 1850–1879,
1.2.1.2 Choice of reference period
yellow curve in this figure corresponds to the orange curve in Figure 2. Source: SR1.5, Figure 1.2.
prior to the largest eruptions, are less than 0.01°C from the average
Any choice of reference period used to approximate ‘pre- for 1850–1900. Temperatures rose by 0.0°C–0.2°C from 1720–
industrial’ conditions is a compromise between data coverage 1800 to 1850–1900 (Hawkins et al., 2017), but the anthropogenic
1.0
and representativeness of typical pre-industrial solar and volcanic contribution to this warming is uncertain (Abram et al., 2016; Schurer
forcing conditions. This report adopts the 51-year reference period, et al., 2017). The 18th century represents a relatively cool period in
0.8
1850–1900 inclusive, assessed as an approximation of pre-industrial the context of temperatures since the mid-Holocene (Marcott et al.,levels in AR5 0.6(Box TS.5, Figure 1 of Field et al., 2014). The years 2013; Lüning and Vahrenholt, 2017; Marsicek et al., 2018), which is
1880–1900 are subject to strong but uncertain volcanic forcing, but indicated by the pink shaded region in Figure 1.2.

0.4
57

0.2
0
-0.2
-0.4
-0.6
1978

1982

1986

1990

1994

1998

2002

2006

2010

2014

2018

Figure 4: UAH10 version 6.0 satellite-based global mean lower tropospheric temperature
anomalies.
From January 1979 through November 2018. The linear trend is +0.13 ◦ C /decade. Source: Roy
Spencer.115Apart from the issue of coverage, satellite temperatures have the added advantage of
not being influenced by urban heat island and land use change effects in the way the GMST
is. Urbanization is currently leading to rapid temperature change in many cities around theworld relative to the surrounding rural areas. Recent research comparing urban and ruraltemperature trends on different continents has provided evidence that urban heat islandeffects have previously been underestimated and that the relative warmth of the mid-20th
century warm period at rural observing stations was comparable to the recent warm period.14 This result is consistent with recent independent findings for the global sea surface
temperature – see next section.

Observations of ocean warming
The temperature graphs in Figures 1–3 have not separated the GMST into its land and sea
components. An example of a plot where these components are separated is shown in Figure 5. Examining the period 1900–1980 (no comment will be made here on the data-sparse
period 1850–1900), it is seen that the land and sea-surface temperatures (SSTs) rose and fell
at the same rate over multi-decadal periods. From 1980 onward, a strong divergence appears, with the land temperatures rising much faster than the SSTs. Taken without reference
to the urban heat island and land use change effects mentioned above, the land temperatures in this period appear to exhibit a GHG-induced signal that has risen well above thebounds of natural variability.
It is not possible to make such an assertion with the same degree of confidence in respectof the sea-surface temperatures. A simple calculation using raw sea-surface temperature
data15 shows that the average SST for the period 2000–2014 (before the onset of the recent
El Niño) was only 0.36◦ C warmer than the average for the period 1936–1950. In the light of
the full 1850–2018 graph, it can be seen that this small degree of SST warming, though consistent with GHG-induced warming with low climate sensitivity, does not unambiguously
exceed the bounds of natural variability.
Recently, results of an extensive ocean data study carried out at the European Centre for
Medium Range Weather Forecasts (ECMWF) have been published. 17,18 The study involved
rescuing over two million station-days of surface data and importing them into the most
up-to-date data-assimilation system. The results for the upper ocean heat content (OHC;
top 300 m) for the period 1900–2010 are shown in Figure 6. This figure shows that the OHC(0–300 m) reached values during the period 1935–1955 that exceed any reached during theperiod 2000–2010. These results clearly suggest the possibility that the natural variability of
OHC (0–300 m), and hence of the closely related global SST, is greater than had previously
been estimated.
These results were not referred to in the SR1.5 report, although the important Laloyaux
et al. paper was accepted for publication well before the deadline for inclusion.

6 Related lines of evidence: GCM modelling
Model tuning (setting of parameters)
It was pointed out in Section 2 that the AR5 attribution statement for the post-1950 warming
is primarily GCM-based, and in Section 4 that SR1.5 also used GCM results to provide supplementary evidence that the warming of recent decades is human-induced. However, some6

Anomaly (◦ C)

1.0
0.5
0.0

-0.5
-1.0

1850
Combined

1900
Land

1950
Sea

2000

Figure 5: Land, sea and combined temperature measurements.
Global 12-month running mean temperature anomalies relative to the 1961-1990 mean. Black:
land and sea temperature (HadCRUT4). Green: land surface air temperature (CRUTEM4). Blue:
SST (HadSST3). Redrawn from Osborn et al. 16

1.65

Heat content (1010 J/m2 )

1.64

1.63

1.62

1.61

1.60

1910

1930

1950

1970

1990

2010

Figure 6: Global average ocean heat content for the upper 300 m.
From the ECMWF CERA-20C reanalysis ensemble, and redrawn from Laloyaux et al. Figure 10.

7very important papers published since the Fifth Assessment Report give reasons to exercise
great caution in using GCM results to attribute warming to human causes. Examples are• ‘Climate scientists open up their black boxes to scrutiny’, by Voosen 19• ‘The art and science of climate model tuning’, by Hourdin et al.20• ‘Uncertainty in model climate sensitivity traced to representations of cumulus precipitation microphysics’, by Zhao et al. 21
These papers, none of which was referred to in SR1.5, point out that relatively smallchanges to the parameter settings in the representations of subgrid-scale physical processes
in GCMs can lead to large changes in the models’ rate of warming in response to increasing GHGs. The Voosen paper reports an example in which modifying a poorly-determinedparameter controlling how fast fresh air mixes into clouds changed the climate sensitivity –the equilibrium warming resulting from a doubling of carbon dioxide levels – of the model inquestion from 3.5◦ C to 7◦ C. The Hourdin et al. paper makes it clear that what modellers do inpractice is to tune their GCMs empirically so that they reproduce the observed 20th century
warming, while giving a value of equilibrium climate sensitivity that lies in ‘an anticipatedacceptable range’. The Zhao et al. paper shows that by tuning the convective precipitation
parameterisation in their GCM they could change its climate sensitivity by a factor of almost
two, without any clear observational constraint that they could find favouring one versionof the model over the others.
Tunings that have enabled models to successfully reproduce the late 20th century warming have not enabled them to reproduce either the marked early 20th century warming or
the recent slow rate of tropospheric warming. Examples of model deficiency in the formercase are shown in Figure 3 (for GMST) and Figure 7 (for SST), and in the latter case in Figure 8.

Temperature anomaly (◦ C)

1.5

1.0

0.5

0

-0.5
1850

1910
Observations

1960

2010

CMIP5 models, natural andanthropogenic forcings

Figure 7: SSTs: modelled and observed.
The modelled warming rate differs by a factor of about four from the observed rate in the
period 1910–1945 (shaded grey). Adapted from figure in the Fifth Assessment Report. 22

8

2.0

Temperature anomaly (◦ C)

1.5

1.0

0.5

0

1977

1982
1987
Models

1992
1997
Satellites

2002

2007
2012
Reanalyses

2017
2022
Balloons

Figure 8: Tropical mid-tropospheric temperatures, models vs. observations.
Models in pink, against various observational datasets in shades of blue. Five-year averages
1979–2016. Trend lines cross zero at 1979 for all series. Adapted from Figure 2 of Dr. John
Christy’s testimony to the U.S. House of Representatives Committee on Science, Space andTechnology, 29 March 2017.23

The Hourdin et al. paper referred to above was the result of a World Meteorological Organization workshop on model tuning. Its fourteen authors represent a broad international
spectrum of climate modellers. The paper points out that the tuning strategy used in themodels whose climate projections were used in the Fifth Assessment (and again in SR1.5)
was not part of the IPCC’s required documentation. The authors explicitly refer to this as a‘lack of transparency’.
Clearly, any agreement (as indicated for recent decades in Figure 3) between the warming observed over a given period and the GHG-driven warming from GCMs that have been
tuned to agree with the observations for that period does not constitute evidence that theobserved warming is GHG-driven.

Some recent independent estimates of climate sensitivity
As mentioned above, equilibrium climate sensitivity (ECS) is the eventual warming that would
take place if the carbon dioxide content of the atmosphere were hypothetically doubled andthen held fixed. ECS is the most important metric in climate science. It is an indicator of how
much warming would take place for any actual increase in CO2.
The true value of ECS is unknown. IPCC AR5 states that its value is likely to lie in therange of 1.5–4.5◦ C, with no best estimate being possible because of a ‘lack of agreement
on values across assessed lines of evidence’. 24 The 1.5–4.5◦ C estimated range, based mainly
on results from GCMs, is unchanged from that given in the IPCC’s First Assessment Report9in 1990. In view of our current knowledge regarding empirical tuning of climate models toachieve desired results, it is clear that estimates of ECS from these models should not betaken as representing an outcome of basic physics.
An independent method of estimating ECS is to use a simple global energy balance
model in conjunction with observations of the global mean values of radiative forcing, ocean
heat uptake and temperature change over a base period and a final period. A recent example of this method cited in the SR1.5 report is the study by Lewis and Curry. 25 They found an
ECS value of 1.5◦ C with an estimated uncertainty range of (1.05–2.45) ◦ C . However, although
SR1.5 referred to the study, it did not judge the result to be of sufficient weight to revise thelower bound of the IPCC AR5 estimated range, because it represented only ‘a single line ofevidence’.
A separate line of evidence indicating that the value of ECS lies below the lower boundof the IPCC AR5 estimated range comes from studies that use recent satellite observationsof the Earth’s tropical radiative response coefficient (change in outgoing top-of-atmosphereradiation in response to a unit change in surface temperature) in conjunction with two-zone(tropical/extratropical) energy balance models. Examples are found in the papers by Lindzen
and Choi26 and Bates;27 the Bates paper uses observational estimates of the tropical longwave radiative response coefficient from both the Lindzen and Choi and the more recent
Mauritsen and Stevens paper.28 The results of the Lindzen–Choi and Bates studies suggest
a value for ECS of around 1◦ C or even below. The SR1.5 report did not refer to any of thesestudies.
There are good reasons, however, why these studies should have been accepted as providing a valid line of evidence. In the first place, the deficiencies they highlight in the GCMs’
representation of the Earth’s tropical longwave radiative response coefficient are very marked;
see Figure 9.
This figure shows clearly how seriously the GCMs underestimate the Earth’s longwave
radiative response to surface temperature variations in the tropics. The two-zone models
indicate that such an underestimation leads to substantial overestimation of ECS.
In the second place, the low climate sensitivity indicated by the two-zone energy balance
models is consistent with the recent observational findings that current global temperatures(GMST and SST) are little warmer than they were around the middle of the last century.

7 Conclusions
The SR1.5 report represents a very significant departure from previous IPCC reports in the
direction of increased alarm regarding global warming, particularly as compared with theFifth Assessment. No rigorous justification for this departure has been provided.
In reality, since the Fifth Assessment considerable evidence has accumulated suggesting that global warming is more of a long-term threat than a planetary emergency. This evidence consists mainly of observational results suggesting lower climate sensitivity (i.e. lesswarming in response to any given increase in greenhouse gas concentrations) and results
indicating a greater contribution from natural variability to explaining observed global temperature trends. The IPCC has not passed on this evidence to policymakers in its SR1.5 report.
The report has also not passed on to policymakers some very important information
published by climate modellers since the last IPCC assessment report regarding the empirical tuning of global climate models to achieve desired results. The failure of previous IPCC
reports to document the models’ tuning procedures has been described by these modellers
10Radiative response coefficient (W/{m 2 K})

7

Lindzen & Choi

Mauritsen & Stevens

6
5
4
3
2
1
0

Observations

CMIP models

Figure 9: Longwave radiative response coefficient in the tropics.
The figure compares the uncertainty ranges for observed (satellites) and modelled radiative
response coefficient from Lindzen and Choi (2011) and Mauritsen and Stevens (2015). The
uncertainty intervals are marked by either arrows (showing outer limits) or bars (showing one
standard error). The magnitudes shown correspond to values given in Table 1 of Bates (2016).
Reproduced from Figure 2 of Park and Choi (2017). 29

as a ‘lack of transparency’. The projections of future warming published by the IPCC are completely dependent on the reliability of these models.
In view of these deficiencies, the SR1.5 report does not merit being regarded by policymakers as a scientifically rigorous document. There is much recent scientific evidence, notreferred to in the report, to support a more considered mitigation strategy than the extreme
measures proposed in the report.
Meanwhile, the worthy goals discussed in the report, such as sustainable development,poverty eradication and reducing inequalities, should be pursued on their own merits andnot made dependent on unsettled climate science.

11

Notes
1. IPCC. Global Warming of 1.5◦ C: An IPCC Special Report on the impacts of global warming of 1.5 ◦ Cabove pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development, and efforts to eradicate poverty. World Meteorological Organization, Geneva, Switzerland, 2018. https://www.ipcc.ch/sr
15/.
2. Stocker TF et al. (eds) Climate Change 2013: The Physical Science Basis. Contribution of Working
Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge
University Press, 2013. The sentence quoted comes from the Summary for Policymakers, p. 17
3. Results presented in WGI AR5 Figure 10.4 and shown schematically in Figure 10.5.
4. Specifically, in relation to the average of the base period 1850–1900, referred to as ‘pre-industrial’.
5. The qualifier ‘essentially all’ is quantified in the ‘Results and discussion’ section of a paper by
Haustein et al. (2017). That paper is the source of the human-induced warming estimated using asimple globally-averaged model and shown in Figures 1, 2 and 3. Haustein, K. et al. A real-time Global
Warming Index. Scientific Reports 2017; 7(1): 15417.
6. Estimated global average of near-surface air temperatures over land and sea-ice, and sea surface
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7. Haustein et al., Figure 1.
8. Otto, FEL et al., Embracing uncertainty in climate change policy. Nature Climate Change 2015; 5:
917–920.
9. Haustein et al. op. cit.
10. University of Alabama in Huntsville.
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tps://www.infona.pl/resource/bwmeta1.element.elsevier-897b3366-77be-34b6-accc-74d1d251db
71
15. For HadSST3 (available at the KNMI Climate Explorer website; https://climexp.knmi.nl/start.cgi).
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Weather 2017: 72(11): 323–329.
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2018, pp. 6–7.
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22. IPCC Fifth Assessment (2013), Working Group 1 report, Fig. 10.21.
23. Christy’s testimony was republished in Climate Science: Assumptions, policy implications, and thescientific method. Report No. 24, Global Warming Policy Foundation, 2017.
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26. Lindzen RS and Choi Y. ‘On the observational determination of climate sensitivity and its implications’. Asia-Pacific Journal of Atmospheric Science 2011; 47: 377–390.
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and high climate sensitivity in models’. Nature Geoscience 2015; 8: 346-351.
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About the Global Warming Policy Foundation
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The Really Inconvenient Truth or ‘It Ain’t Necessarily So’
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Is Global Warming the Number One Threat to Humanity?
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The Climate Model and the Public Purse
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UK Energy Security: Myth and Reality
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On the Beach
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Floods and Droughts in the Indian Monsoon
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Twenty Good Reasons not to Worry about Polar Bears
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Climate Models for the Layman
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Germany’s Energiewende : a Disaster in the Making
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Truly Green?
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20 Good Reasons not to Worry About Polar Bears: Update
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Sacrificing the Poor: The Lancet on ‘pollution’
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Kicking Away the Energy Ladder
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Flaws in Applying Greenhouse Warming to Climate Variability
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Save the Oceans: Stop Recycling Plastic
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Small Modular Nuclear: Crushed at Birth
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Quakes, Pollution and Flaming Faucets
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DEFRA vs Met Office: Factchecking the State of the UK Climate
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